arXiv subjects

Praful D. Mankar

Publications and source records attributed to Praful D. Mankar.

At least 19 recordsLinked to original sources

arXiv2026

Near-field Wideband Multi-User Localization using NFMR-Net

This paper proposes a deep learning based method for wideband near-field multi-user localization. In particular, the proposed approach utilizes the Zadoff-Chu (ZC) sequence based pilots to mitigate the inter-user interference, which in turn aids the estimation of the multi-tap channel matrix. From this channel matrix, we extract the line-of-sight (LoS) array response based on the delay-tap energy profile. The LoS delay-tap is further refined using parabolic interpolation to obtain the coarse estimate of range parameter. Next, the extracted LoS array response is used to obtain the coarse angle estimate using 2D MUSIC algorithm. These coarse estimates are further refined using the near-field music refinement network (NFMR-Net), which involves separate sub-networks for range and angle estimations. Through numerical analysis, the proposed NFMR-Net is demonstrated to outperform conventional 2D MUSIC algorithm.

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arXiv2026

Time-Frequency Pilot Sequence Design and LoS Delay-Doppler Estimation

We present a novel framework for line-of-sight (LoS) delay-Doppler (DD) estimation in dense scattering propagation environments. We present two time-frequency (TF) domain pilot sequences inspired by the Zadoff-Chu sequence that exhibit desirable autocorrelation properties. Further, we present a twisted convolution-based approach for LoS DD estimation directly from the TF-domain received signal, avoiding an additional TF to DD transformation, which is commonly found in literature. Numerical results from simulations demonstrate that the proposed framework significantly outperforms traditional single-carrier Zadoff-Chu sequences in both delay and Doppler estimation over a wide range of Rician fading factor and SNR values.

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arXiv2025

Near-field Anchor-free Localization using Reconfigurable Intelligent Surfaces

Near-field localization is expected to play a crucial role in enabling a plethora of applications under the paradigm of 6G networks. The conventional localization methods rely on complex infrastructure for providing cooperative anchor nodes that often contribute to higher network overload and energy consumption. To address this, the passive reconfigurable intelligent surfaces (RISs) can be leveraged as perfectly synced reference nodes for developing anchor-free near-field localization. First, we obtain the optimal RIS configurations that maximizes the block-wise averaged trace of Fisher information matrix so that localization error variance can be minimized across the area-of-interest (AoI). Next, we present a two-stage anchor-free localization framework wherein first a coarse estimate is obtained using cosine similarity between the coarse grid and the signal received under pre-defined optimal RIS configurations. In second stage, we refine solution similarly using a finer grid constructed around the coarse estimate. The numerical results show that the proposed RIS-aided anchor-free localization provides small root mean square error for practical values of signal-to-noise ratio (SNR), RIS dimension, and number of antennas at user.

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arXiv2025

Capacity Analysis of Cascaded BD-RIS Assisted MIMO Systems

This paper examines the cascaded deployment of beyond diagonal (BD) reconfigurable intelligent surfaces (RISs) and explores its potential to enhance the performance of MIMO systems. We first derive the jointly optimal closed form solutions for the RISs in cascade with SVD water filling (SVD WF) and uniform power allocation (UPA) precoding strategies. The optimally configured cascaded-RIS with UPA is shown to achieve performance comparable to that with the SVD WF approach, suggesting that cascaded-RISs can also aid in reducing transmitter complexity. Furthermore, the approximate ergodic capacity for UPA is derived, along with its high SNR approximation which provides multiple useful insights into the dimension and deployment of cascaded RISs. The analytical results establish a clear tradeoff among transmit power, RIS size, and achievable capacity, providing insights for practical deployment in high SNR cascaded RIS MIMO systems.

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arXiv2025

Near-field 5D Pose Estimation using Reconfigurable Intelligent Surfaces

The advent of 6G is expected to enable many use cases which may rely on accurate knowledge of the location and orientation of user equipment (UE). The conventional localization methods suffer from limitations such as synchronization and high power consumption required for multiple active anchors. This can be mitigated by utilizing a large dimensional passive reconfigurable intelligent surface (RIS). This paper presents a novel low-complexity approach for the estimation of 5D pose (i.e. 3D location and 2D orientation) of a UE in near-field RIS-assisted multiple-input multiple-output (MIMO) systems. The proposed approach exploits the symmetric arrangement of uniform planar array of RIS and uniform linear array of UE to decouple the 5D problem into five 1D sub-problems. Further, we solve these sub-problems using a total least squares ESPRIT inspired approach to obtain closed-form solutions.

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arXiv2024

Maximum Eigenvalue Detection based Spectrum Sensing in RIS-aided System with Correlated Fading

Robust spectrum sensing is crucial for facilitating opportunistic spectrum utilization for secondary users (SU) in the absense of primary users (PU). However, propagation environment factors such as multi-path fading, shadowing, and lack of line of sight (LoS) often adversely affect detection performance. To deal with these issues, this paper focuses on utilizing reconfigurable intelligent surfaces (RIS) to improve spectrum sensing in the scenario wherein both the multi-path fading and noise are correlated. In particular, to leverage the spatially correlated fading, we propose to use maximum eigenvalue detection (MED) for spectrum sensing. We first derive exact distributions of test statistics, i.e., the largest eigenvalue of the sample covariance matrix, observed under the null and signal present hypothesis. Next, utilizing these results, we present the exact closed-form expressions for the false alarm and detection probabilities. In addition, we also optimally configure the phase shift matrix of RIS such that the mean of the test statistics is maximized, thus improving the detection performance. Our numerical analysis demonstrates that the MED's receiving operating characteristic (ROC) curve improves with increased RIS elements, SNR, and the utilization of statistically optimal configured RIS.

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arXiv2024

Peak Age of Information under Tandem of Queues

This paper considers a communication system where a source sends time-sensitive information to its destination via queues in tandem. We assume that the arrival process as well as the service process (of each server) are memoryless, and each of the servers has no buffer. For this setup, we develop a recursive framework to characterize the mean peak age of information (PAoI) under preemptive and non-preemptive policies with $N$ servers having different service rates. For the preemptive case, the proposed framework also allows to obtain mean age of information (AoI).

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arXiv2024

Characterization of Capacity and Outage of RIS-aided Downlink Systems under Rician Fading

This letter presents optimal beamforming and outage analysis for a Reconfigurable Intelligent Surface (RIS)-aided multiple input single output downlink system under Rician fading on both the direct and the RIS-assisted indirect links. We focus on maximizing the capacity for two transmitter architectures: fully digital (FD) and fully analog (FA). This capacity maximization problem with optimally configured RIS is shown to be $L_1$ norm-maximization with respect to the transmit beamformer. To obtain the optimal FD beamformer, we propose a complex $L_1$-PCA-based algorithm whose complexity is significantly lower than the existing semi-definite relaxation-based solutions. We also propose a low-complexity optimal beamforming algorithm to obtain the FA beamformer solution. Further, we derive analytical upper bounds on the SNR achievable by the proposed algorithms and utilize them to characterize the lower bounds on outage probabilities. The derived bounds are numerically shown to closely match the achievable performance for a low-rank channel matrix and are shown to be exact for a unit-rank channel matrix.

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arXiv2024

Capacity Maximization for RIS-assisted Multi-user MISO Communication Systems

We consider a multi-user multiple input single output (MU-MISO) system assisted by a reconfigurable intelligent surface (RIS). For such a system, we aim to optimally select the RIS phase shifts and precoding vectors for maximizing the effective rank of the weighted channel covariance matrix which in turn improves the channel capacity. For a low-complex transmitter design, we employ maximum ratio transmission (MRT) and minimum-mean square error (MMSE) precoding schemes along with water-filling algorithm-based power allocation. Further, we show that MRT and MMSE exhibit equivalent performance and become optimal when the channel effective rank is maximized by optimally configuring the RIS consisting of a large number of elements.

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arXiv2024

RIS-NOMA integrated low-complexity transceiver architecture: Sum rate and energy efficiency perspective

This paper aims to explore reconfigurable intelligent surface (RIS) integration in a millimeter wave (mmWave) communication system with low-complexity transceiver architecture under imperfect CSI assumption. Towards this, we propose a RIS-aided system with a fully analog (FA) architecture at the base station. However, to overcome the disadvantage of single-user transmission due to the single RF-chain, we employ NOMA. For such a system, we formulate sum rate (SR) and energy efficiency (EE) maximization problems to obtain the joint transmit beamformer, RIS phase shift matrix, and power allocation solutions under minimum rate constraint. We first tackle the fractional objectives of both problems by reformulating the SR and EE maximization problems into equivalent quadratic forms using the quadratic transform. On the other hand, we employ successive convex approximation and the semi-definite relaxation technique to handle the non-convex minimum rate and unit modulus constraint of the RIS phase shifts, respectively. Next, we propose an alternating optimization-based algorithm that iterates over the transmit beamformer, power allocation, and RIS phase shift subproblems. Further, we also show that the quadratic reformulation is equivalent to the WMSE-based reformulation for the case of SR maximization problem. Our numerical results show that the proposed RIS-NOMA integrated FA architecture system outperforms the optimally configured fully digital architecture in terms of SR at low SNR and EE for a wide range of SNR while still maintaining low hardware complexity and cost. Finally, we present the numerical performance analysis of the RIS-NOMA integrated low-complexity system for various system configuration parameters.

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arXiv2023

Statistically Optimal Beamforming and Ergodic Capacity for RIS-aided MISO Systems

This paper focuses on optimal beamforming to maximize the mean signal-to-noise ratio (SNR) for a reconfigurable intelligent surface (RIS)-aided MISO downlink system under correlated Rician fading. The beamforming problem becomes non-convex because of the unit modulus constraint of passive RIS elements. To tackle this, we propose a semidefinite relaxation-based iterative algorithm for obtaining statistically optimal transmit beamforming vector and RIS-phase shift matrix. Further, we analyze the outage probability (OP) and ergodic capacity (EC) to measure the performance of the proposed beamforming scheme. Just like the existing works, the OP and EC evaluations rely on the numerical computation of the iterative algorithm, which does not clearly reveal the functional dependence of system performance on key parameters. Therefore, we derive closed-form expressions for the optimal beamforming vector and phase shift matrix along with their OP performance for special cases of the general setup. Our analysis reveals that the i.i.d. fading is more beneficial than the correlated case in the presence of LoS components. This fact is analytically established for the setting in which the LoS is blocked. Furthermore, we demonstrate that the maximum mean SNR improves linearly/quadratically with the number of RIS elements in the absence/presence of LoS component under i.i.d. fading.

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arXiv2023

Coding Gain for Age of Information in a Multi-source System with Erasure Channel

In our work, we study the age of information ($\AoI$) in a multi-source system where $K$ sources transmit updates of their time-varying processes via a common-aggregator node to a destination node through a channel with packet delivery errors. We analyze $\AoI$ for an $(α, β, ε_0, ε_1)$-Gilbert-Elliot ($\GE$) packet erasure channel with a round-robin scheduling policy. We employ maximum distance separable ($\MDS$) scheme at aggregator for encoding the multi-source updates. We characterize the mean $\AoI$ for the $\MDS$ coded system for the case of large blocklengths. We further show that the \emph{optimal coding rate} that achieves maximum \emph{coding gain} over the uncoded system is $n(1-\pers)-\smallO(n)$, where $\pers \triangleq \fracβ{α+β}ε_0 + \fracα{α+β}ε_1$, and this maximum coding gain is $(1+\pers)/(1+\smallO(1))$.

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arXiv2022

Age of Information with On-Off Service

This paper considers a communication system where a source sends time-sensitive information to its destination. We assume that both arrival and service processes of the messages are memoryless and the source has a single server with no buffer. Besides, we consider that the service is interrupted by an independent random process, which we model using the On-Off process. For this setup, we study the age of information for two queueing disciplines: 1) non-preemptive, where the messages arriving while the server is occupied are discarded, and 2) preemptive, where the in-service messages are replaced with newly arriving messages in the Off states. For these disciplines, we derive closed-form expressions for the mean peak age and mean age.

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arXiv2022

Optimal Beamforming and Outage Analysis for Max Mean SNR under RIS-aided Communication

This paper considers beamforming for a reconfigurable intelligent surface (RIS)-aided multiple input single output (MISO) communication system in the presence of Rician multipath fading. Our aim is to jointly optimize the transmit beamformer and RIS phase shift matrix for maximizing the mean signal-to-noise (SNR) of the combined signal received over direct and indirect links. While numerical solutions are known for such optimization problems, this is the first paper to derive closed-form expressions for the optimal beamformer and the phase shifter for a closely related problem. In particular, we maximize a carefully constructed lower bound of the mean SNR, which is more conducive to analytical treatment. Further, we show that effective channel gain under optimal beamforming follows Rice distribution. Next, we use these results to characterize a closed-form expression for the outage probability under the proposed beamforming scheme, which is subsequently employed to derive an analytical expression for the ergodic capacity. Finally, we numerically demonstrate the efficacy of the proposed beamformer solution in comparison with the existing algorithmically obtained optimal solution for the exact mean SNR maximization.

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arXiv2022

Deep Learning based Coverage and Rate Manifold Estimation in Cellular Networks

This article proposes Convolutional Neural Network-based Auto Encoder (CNN-AE) to predict location-dependent rate and coverage probability of a network from its topology. We train the CNN utilising BS location data of India, Brazil, Germany, and the USA and compare its performance with stochastic geometry (SG) based analytical models. In comparison to the best-fitted SG-based model, CNN-AE improves the coverage and rate prediction errors by a margin of as large as $40\%$ and $25\%$ respectively. As an application, we propose a low complexity, provably convergent algorithm that, using trained CNN-AE, can compute locations of new BSs that need to be deployed in a network in order to satisfy pre-defined spatially heterogeneous performance goals.

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arXiv2021

Adaptive Rate NOMA for Cellular IoT Networks

Internet-of-Things (IoT) technology is envisioned to enable a variety of real-time applications by interconnecting billions of sensors/devices deployed to observe some random physical processes. These IoT devices rely on low-power wide-area wireless connectivity for transmitting, mostly fixed- but small-size, status updates of their associated random processes. The cellular networks are seen as a natural candidate for providing reliable wireless connectivity to IoT devices. However, the conventional orthogonal multiple access (OMA) to these massive number of devices is expected to degrade the spectral efficiency. As a promising alternative to OMA, the cellular base stations (BSs) can employ non-orthogonal multiple access (NOMA) for the uplink transmissions of mobile users and IoT devices. In particular, the uplink NOMA can be configured such that the mobile user can adapt transmission rate based on its channel condition while the IoT device transmits at a fixed rate. For this setting, we analyze the ergodic capacity of mobile users and the mean local delay of IoT devices using stochastic geometry. Our analysis demonstrates that the above NOMA configuration can provide better ergodic capacity for mobile users compare to OMA when IoT devices' delay constraint is strict. Furthermore, we also show that NOMA can support a larger packet size for IoT devices than OMA under the same delay constraint.

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arXiv2021

Throughput and Age of Information in a Cellular-based IoT Network

This paper studies the interplay between device-to-device (D2D) communications and real-time monitoring systems in a cellular-based Internet of Things (IoT) network. In particular, besides the possibility that the IoT devices communicate directly with each other in a D2D fashion, we consider that they frequently send time-sensitive information/status updates (about some underlying physical processes) to their nearest base stations (BSs). By modeling the locations of the IoT devices as a bipolar Poisson Point Process (PPP) and that of the BSs as another independent PPP, we characterize the performance of the D2D links and status update links in terms of network throughput and Age-of-Information (AoI), respectively. We consider a maximum power constraint and distance-dependent fractional power control for all status update transmissions. Hence, the locations of the IoT devices allowed to send status updates are constrained to lie within the Johnson-Mehl cells. For this set-up, the average network throughput is obtained by deriving the mean success probability of the D2D links, whereas the spatial moments of the temporal mean AoI are obtained by deriving the moments of the temporal means of both success and scheduling probabilities of the status update links.

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arXiv2021

Spatial Distribution of the Mean Peak Age of Information in Wireless Networks

This paper considers a large-scale wireless network consisting of source-destination (SD) pairs, where the sources send time-sensitive information, termed status updates, to their corresponding destinations in a time-slotted fashion. We employ Age of information (AoI) for quantifying the freshness of the status updates measured at the destination nodes for two different queuing disciplines, namely Type I and II queues. Type I queue is assumed to transmit the status updates in a first-come-first-served (FCFS) fashion with no storage facility. However, Type I queue may not necessarily minimize AoI because a new update will not be allowed to enter a server until the current update has been successfully transmitted. To overcome this shortcoming, we consider Type II queue in which the most recent status update available at a given transmission slot is transmitted in order to minimize the AoI. As the update delivery rate for a given link is a function of the interference field seen from the receiver, the temporal mean AoI can be treated as a random variable over space. Our goal in this paper is to characterize the spatial distribution of the mean AoI observed by the SD pairs by modeling them as a Poisson bipolar process. Towards this objective, we first derive accurate bounds on the moments of success probability while efficiently capturing the interference-induced coupling in the activities of the SD pairs. Using this result, we then derive tight bounds on the moments as well as the spatial distribution of peak AoI. Our numerical results verify our analytical findings and demonstrate the impact of various system design parameters on the mean peak AoI.

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